Big Data Data Mining and Machine Learning

Author: Jared Dean
Publisher: John Wiley & Sons
ISBN: 9781118920701
Release Date: 2014-05-07
Genre: Computers

With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

Big Data Data Mining and Machine Learning

Author: Jared Dean
Publisher: CreateSpace
ISBN: 1502462915
Release Date: 2014-09-23
Genre: Computers

With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

Performance Dashboards

Author: Wayne W. Eckerson
Publisher: John Wiley & Sons
ISBN: 047091842X
Release Date: 2010-10-07
Genre: Business & Economics

Tips, techniques, and trends on harnessing dashboard technology to optimize business performance In Performance Dashboards, Second Edition, author Wayne Eckerson explains what dashboards are, where they can be used, and why they are important to measuring and managing performance. As Director of Research for The Data Warehousing Institute, a worldwide association of business intelligence professionals, Eckerson interviewed dozens of organizations that have built various types of performance dashboards in different industries and lines of business. Their practical insights explore how you can effectively turbo-charge performance–management initiatives with dashboard technology. Includes all-new case studies, industry research, news chapters on "Architecting Performance Dashboards" and "Launching and Managing the Project" and updated information on designing KPIs, designing dashboard displays, integrating dashboards, and types of dashboards. Provides a solid foundation for understanding performance dashboards, business intelligence, and performance management Addresses the next generation of performance dashboards, such as Mashboards and Visual Discovery tools, and including new techniques for designing dashboards and developing key performance indicators Offers guidance on how to incorporate predictive analytics, what-if modeling, collaboration, and advanced visualization techniques This updated book, which is 75% rewritten, provides a foundation for understanding performance dashboards, business intelligence, and performance management to optimize performance and accelerate results.

Unleashing Your Inner Leader

Author: Vickie Bevenour
Publisher: John Wiley & Sons
ISBN: 9781119047032
Release Date: 2015-01-26
Genre: Business & Economics

Leverage your brand of leadership for maximum results Unleashing Your Inner Leader: Executive Coach Tells All presents the premise that there is a powerful leader inside each of us. The focus is on real life exercises and case studies to help you discover, release, and leverage your inner leader: to reach heights in your career that you never thought possible. The book discusses the individual’s impact on the organization and which professional behaviors most frequently demonstrate leadership competencies. Conduct a “forensic intervention” to find out what is going awry in your professional development, or what has gone wrong in the past, and craft a strategy to overcome obstacles, gain unmistakable clarity about yourself, and focus your abilities to match organizational needs. Great leaders start their assessments from the inside out, and their passion is so strong that it permeates their organizations and builds the culture, regardless of rank. They inspire their teams by sharing the spotlight and encouraging coworkers to excel, operating with clean authenticity to maximize results. Unleashing Your Inner Leader helps you recognize where you fall on the leadership spectrum, and provides practical advice for shaping your brand of leadership to capitalize on your authentic capability and potential. You’ll find expert insight as an executive business coach guides you to: Evaluate your strengths, values, and personal impact to craft a vision for the world around you Discover what’s holding you back from maximum effectiveness Tap into your undiscovered potential, and inspire your team to excellence Recognize what it will take to move you and your organization to the next level It is often very difficult for leaders to see their own greatness, unlock it, and use it in a practical way to get results. Be the spark that ignites your team, and steer your own development toward becoming an impactful leader with Unleashing Your Inner Leader.

Modern Computational Models of Semantic Discovery in Natural Language

Author: Žižka, Jan
Publisher: IGI Global
ISBN: 9781466686915
Release Date: 2015-07-17
Genre: Computers

Language—that is, oral or written content that references abstract concepts in subtle ways—is what sets us apart as a species, and in an age defined by such content, language has become both the fuel and the currency of our modern information society. This has posed a vexing new challenge for linguists and engineers working in the field of language-processing: how do we parse and process not just language itself, but language in vast, overwhelming quantities? Modern Computational Models of Semantic Discovery in Natural Language compiles and reviews the most prominent linguistic theories into a single source that serves as an essential reference for future solutions to one of the most important challenges of our age. This comprehensive publication benefits an audience of students and professionals, researchers, and practitioners of linguistics and language discovery. This book includes a comprehensive range of topics and chapters covering digital media, social interaction in online environments, text and data mining, language processing and translation, and contextual documentation, among others.

Big Data For Dummies

Author: Judith Hurwitz
Publisher: John Wiley & Sons
ISBN: 9781118644171
Release Date: 2013-04-02
Genre: Computers

Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

Strategies in Biomedical Data Science

Author: Jay A. Etchings
Publisher: John Wiley & Sons
ISBN: 9781119256182
Release Date: 2017-01-03
Genre: Medical

An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entails Explore the available advanced analytic resources and tools Learn how bioinformatics as a service is quickly becoming reality Examine the future of IOT and the deluge of personal device data The sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.

Too Big to Ignore

Author: Phil Simon
Publisher: John Wiley & Sons
ISBN: 9781118641866
Release Date: 2013-03-05
Genre: Business & Economics

Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior. How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions. It's time to start thinking big. In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

Creating Value with Big Data Analytics

Author: Peter C. Verhoef
Publisher: Routledge
ISBN: 9781317561927
Release Date: 2016-01-08
Genre: Business & Economics

Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

A Practical Guide to Data Mining for Business and Industry

Author: Andrea Ahlemeyer-Stubbe
Publisher: John Wiley & Sons
ISBN: 9781118763377
Release Date: 2014-03-31
Genre: Mathematics

Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.

Data Mining and Statistics for Decision Making

Author: Stéphane Tufféry
Publisher: John Wiley & Sons
ISBN: 0470979283
Release Date: 2011-03-23
Genre: Computers

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Big Data Mining and Analytics

Author: Stephan Kudyba
Publisher: CRC Press
ISBN: 9781466568716
Release Date: 2014-03-12
Genre: Computers

There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitating a clear understanding of big data, it supplies authoritative insights from expert contributors into leveraging data resources, including big data, to improve decision making. Illustrating basic approaches of business intelligence to the more complex methods of data and text mining, the book guides readers through the process of extracting valuable knowledge from the varieties of data currently being generated in the brick and mortar and internet environments. It considers the broad spectrum of analytics approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport, Distinguished Professor, Babson College; Fellow, MIT Center for Digital Business; and Co-Founder, International Institute for Analytics Introduces text mining and the transforming of unstructured data into useful information Examines real time wireless medical data acquisition for today’s healthcare and data mining challenges Presents the contributions of big data experts from academia and industry, including SAS Highlights the most exciting emerging technologies for big data—Hadoop is just the beginning Filled with examples that illustrate the value of analytics throughout, the book outlines a conceptual framework for data modeling that can help you immediately improve your own analytics and decision-making processes. It also provides in-depth coverage of analyzing unstructured data with text mining methods to supply you with the well-rounded understanding required to leverage your information assets into improved strategic decision making.

The Data Asset

Author: Tony Fisher
Publisher: John Wiley & Sons
ISBN: 0470508027
Release Date: 2009-06-22
Genre: Business & Economics

An indispensable guide that shows companies how to treat data as a strategic asset Organizations set their business strategy and direction based on information that is available to executives. The Data Asset provides guidance for not only building the business case for data quality and data governance, but also for developing methodologies and processes that will enable your organization to better treat its data as a strategic asset. Part of Wiley's SAS Business Series, this book looks at Business Case Building; Maturity Model and Organization Capabilities; 7-Step Programmatic Approach for Success; and Technologies Required for Effective Data Quality and Data Governance and, within these areas, covers Risk mitigation Cost control Revenue optimization Undisciplined and reactive organizations Proactive organizations Analysis, improvement, and control technology Whether you're a business manager or an IT professional, The Data Asset reveals the methodology and technology needed to approach successful data quality and data governance initiatives on an enterprise scale.

Business Process Modeling Simulation and Design Second Edition

Author: Manuel Laguna
Publisher: CRC Press
ISBN: 9781439885253
Release Date: 2013-04-25
Genre: Business & Economics

Most textbooks on business process management focus on either the nuts and bolts of computer simulation or the managerial aspects of business processes. Covering both technical and managerial aspects of business process management, Business Process Modeling, Simulation and Design, Second Edition presents the tools to design effective business processes and the management techniques to operate them efficiently. New to the Second Edition Three completely revised chapters that incorporate ExtendSim 8 An introduction to simulation A chapter on business process analytics Developed from the authors’ many years of teaching process design and simulation courses, the text provides students with a thorough understanding of numerous analytical tools that can be used to model, analyze, design, manage, and improve business processes. It covers a wide range of approaches, including discrete event simulation, graphical flowcharting tools, deterministic models for cycle time analysis and capacity decisions, analytical queuing methods, and data mining. Unlike other operations management books, this one emphasizes user-friendly simulation software as well as business processes, rather than only manufacturing processes or general operations management problems. Taking an analytical modeling approach to process design, this book illustrates the power of simulation modeling as a vehicle for analyzing and designing business processes. It teaches how to apply process simulation and discusses the managerial implications of redesigning processes. The ExtendSim software is available online and ancillaries are available for instructors.